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Ruchkin, Vladislav; Henrich, Christopher C.; Jones, Stephanie M.; Vermeiren, Robert; Schwab-Stone, Mary – Journal of Abnormal Child Psychology, 2007
Understanding the mechanisms underlying the development of violence exposure sequelae is essential to providing effective treatments for traumatized youth. This longitudinal study examined the mediating role of posttraumatic stress in the relationship between violence exposure and psychopathology, and compared the mediated models by gender. Urban…
Descriptors: Structural Equation Models, Posttraumatic Stress Disorder, Psychopathology, Urban Youth
Anthony, Jason L.; Williams, Jeffrey M.; McDonald, Renee; Francis, David J. – Annals of Dyslexia, 2007
Phonological awareness, phonological memory, and phonological access to lexical storage play important roles in acquiring literacy. We examined the convergent, discriminant, and predictive validity of these phonological processing abilities (PPA) in 389 3-, 4-, and 5-year-old children. Confirmatory factor analysis supported the validity of each…
Descriptors: Structural Equation Models, Predictive Validity, Preschool Children, Factor Analysis
Tolley, Patricia Ann Separ – ProQuest LLC, 2009
The purpose of this correlational study was to examine the effects of a residential learning community and enrollment in an introductory engineering course to engineering students' perceptions of the freshman year experience, academic performance, and persistence. The sample included students enrolled in a large, urban, public, research university…
Descriptors: Structural Equation Models, Academic Achievement, Student Surveys, Program Effectiveness
White, Casey B.; Dey, Eric L.; Fantone, Joseph C. – Advances in Health Sciences Education, 2009
Academic achievement indices including GPAs and MCAT scores are used to predict the spectrum of medical student academic performance types. However, use of these measures ignores two changes influencing medical school admissions: student diversity and affirmative action, and an increased focus on communication skills. To determine if GPA and MCAT…
Descriptors: Medical Students, Search Committees (Personnel), Grade Point Average, Medical Schools
Thompson, Bruce; Melancon, Janet G. – 1996
This study investigated the benefits of creating item "testlets" or "parcels" in the context of structural equation modeling confirmatory factor analysis (CFA). Testlets are defined as groups of items related to a single content area that is developed as a unit. The strategy is illustrated using data from the administration of…
Descriptors: Statistical Distributions, Structural Equation Models, Test Construction
Stapleton, Laura M.; Hancock, Gregory R. – 2000
This paper illustrates the differences in inference that can be seen when traditional and multilevel structural equation modeling techniques are applied to hierarchical data. Research on faculty is an area in which multilevel data exist, and where previous research generally has not modeled the nested structure. Using data from the National Study…
Descriptors: College Faculty, Higher Education, Structural Equation Models

Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M. – Structural Equation Modeling, 2003
Demonstrated, through simulation, that stationary autoregressive moving average (ARMA) models may be fitted readily when T>N, using normal theory raw maximum likelihood structural equation modeling. Also provides some illustrations based on real data. (SLD)
Descriptors: Maximum Likelihood Statistics, Simulation, Structural Equation Models

Enders, Craig K. – Multivariate Behavioral Research, 2002
Proposed a method for extending the Bollen-Stine bootstrap model (K. Bollen and R. Stine, 1992) fit to structural equation models with missing data. Developed a Statistical Analysis System macro program to implement this procedure, and assessed its usefulness in a simulation. The new method yielded model rejection rates close to the nominal 5%…
Descriptors: Goodness of Fit, Simulation, Structural Equation Models

MacIntosh, Randall – Educational and Psychological Measurement, 1997
Presents KANT, a FORTRAN 77 software program that tests assumptions of multivariate normality in a data set. Based on the test developed by M. V. Mardia (1985), the KANT program is useful for those engaged in structural equation modeling with latent variables. (SLD)
Descriptors: Computer Software, Data Analysis, Structural Equation Models

Thompson, Bruce – Educational and Psychological Measurement, 1997
A general linear model framework is used to suggest that structure coefficients ought to be interpreted in structural equation modeling confirmatory factor analysis (CFA) studies in which factors are correlated. Two heuristic data sets make the discussion concrete, and two additional studies illustrate the benefits of CFA structure coefficients.…
Descriptors: Factor Analysis, Mathematical Models, Structural Equation Models

McDonald, Roderick P. – Multivariate Behavioral Research, 1997
Structural equation modelling is becoming increasingly popular in education. This article examines and compares a number of alternative assumptions governing nondirected paths in structural equation models without latent variables vis-a-vis a data set on lung ventilation. Some problems with the conventional procedures in path analysis are pointed…
Descriptors: Case Studies, Path Analysis, Structural Equation Models

Hayduk, Leslie; Cummings, Greta; Stratkotter, Rainer; Nimmo, Melanie; Grygoryev, Kostyantyn; Dosman, Donna; Gillespie, Michael; Pazderka-Robinson, Hannah; Boadu, Kwame – Structural Equation Modeling, 2003
Provides an introduction to the structural equation modeling concepts developed by J. Pearl, discussing the concept he calls "d-separation." Explains how d-separation connects to control variables, partial correlations, causal structuring, and even a potential mistake in regression. (SLD)
Descriptors: Causal Models, Correlation, Structural Equation Models, Theories

Raykov, Tenko; Marcoulides, George A.; Boyd, Jeremy – Structural Equation Modeling, 2003
Illustrates how commonly available structural equation modeling programs can be used to conduct some basic matrix manipulations and generate multivariate normal data with given means and positive definite covariance matrix. Demonstrates the outlined procedure. (SLD)
Descriptors: Data Analysis, Matrices, Simulation, Structural Equation Models

Brito, Carlos; Pearl, Judea – Structural Equation Modeling, 2002
Established a new criterion for the identification of recursive linear models in which some errors are correlated. Shows that identification is assured as long as error correlation does not exist between a cause and its direct effect; no restrictions are imposed on errors associated with indirect causes. (SLD)
Descriptors: Correlation, Error of Measurement, Structural Equation Models

McArdle, J. J.; Cattell, Raymond B. – Multivariate Behavioral Research, 1994
Some problems of multiple-group factor rotation based on the parallel proportional profiles and confactor rotation of R. B. Cattell are described, and several alternative modeling solutions are proposed. Benefits and limitations of the structural-modeling approach to oblique confactor resolution are examined, and opportunities for research are…
Descriptors: Factor Analysis, Factor Structure, Structural Equation Models